Effects of advanced surface ablations and intralase femtosecond LASIK on higher order aberrations and visual acuity outcome
Bibliographic record
Abstract
BACKGROUND/AIMS: To study the changes in wavefront (ocular) and corneal higher order aberrations (HOAs) and visual acuity (VA) outcome following wavefront-guided advanced surface ablation (ASA) techniques and intralase femtosecond LASIK (iLASIK) in myopia treatment. METHODS: Ocular aberration and corneal topography of 240 eyes in the ASA techniques (this was equally divided into a flap-on group where the epithelial flap was preserved and reapplied to the photoablated stromal bed and a flap-off group when the epithelial flap was discarded during the procedure), and 138 eyes in the iLASIK group were obtained before and 3 months following treatment. The correlation of aberrations with best spectacle-corrected visual acuity was analyzed. RESULTS: At 3 months, there was statistically significant (P < 0.001) surgically induced increase in spherical aberration (SA) in each of the techniques for both ocular and corneal analysis. iLASIK induced significantly less ocular and corneal HOAs (P < 0.001). The mean manifest refractive spherical equivalent was closer to attempted correction compared to other groups (P < 0.001). Eighty-three eyes (70%) of flap-on, 80 (67%) flap-off and 94 eyes (68%) in the iLASIK group achieved 20/20 uncorrected VA. Fifteen eyes (11%) accomplished 20/12.5 or better in iLASIK compared to 4 (3%) for flap-on and 7 (6%) for flap-off ASA group. Only the flap-off treatment showed a consistent correlation between the corrected aberrations and visual performance. CONCLUSION: At 3 months, all procedures resulted in a significant increase in HOAs and SA. All had comparable 20/20 VA and 11% of iLASIK patients achieved 20/12.5 or better level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".